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  • Introduction to NLP for Classification Task – Session 2

    Online via Zoom

    Recorded Material: Video: https://drive.google.com/file/d/1gBUK_NtU3kSNblsGaYouLHyfDHlxr1tt/view PowerPoint: 2.IntroductiontoNLP,Kagle On Wednesday, July 15, 2020 at 6:00 p.m., IEEE Toronto WIE and Computational Intelligence Society will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 2”. Day & Time: Wednesday, July 15, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In the second session, we will introduce the concept of deep learning, and then specifically focus on Natural Language Process. We will also introduce Kaggle Account as an environment for python coding. Register: Please visit https://events.vtools.ieee.org/m/235444 or https://events.vtools.ieee.org/m/235447 for more details and to register.

  • Advanced Topics on Scalable Deployment of Machine Learning and Drone-Based Search and Rescue

    Online via Zoom Toronto, Ontario Canada

    On Thursday, July 23, 2020 at 1:00 p.m., Dalia Hanna and Mujahid Sultan will be presenting “Advanced Topics on Scalable Deployment of Machine Learning and Drone-Based Search and Rescue”. Day & Time: Thursday, July 23, 2020 1:00 p.m. – 4:00 p.m. Speakers: Dalia Hanna, Mujahid Sultan Organizers: IEEE Toronto WIE, IEEE IM/RA, Ryerson CS Graduate Student Council, IEEE Ryerson Computational Intelligence Chapter, Ryerson CSCU Location: Virtual – Zoom Contact: Ayda Naserialiabadi Title: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Abstract: Unmanned Aerial Vehicles (UAV) are now used in many applications. The focus in this presentation is on their use in public safety, specifically in search and rescue (SAR) operations involving lost persons living with dementia (LPLWD). When it comes to saving lives, there are many human factors associated with UAV operations that impact the performance of expert human SAR teams that could be improved through forms of automation. These include familiarity with the search location, tasks associated with piloting and search/flight management during SAR operations.  A LPLWD may not be interested in assisting in their own rescue as they may not know they are lost. As such, it has been observed that they tend to keep walking until they are faced with an obstacle that bars their further progress. The approach presented in this research work focuses on developing a people finding algorithm to identify higher probability locations where an LPLWD might be found, through informed, behavior-based analysis of the search location; then, developing an algorithm to fly a UAV to the vicinity of these higher probability locations.  The algorithm was tested and validated through field testing. The results from both the data collection process and the field tests indicated that there are efficiencies in using the drone, which enhances the probability of finding the lost person alive.  An informed cleaning process involving both manual and ‘R’-automated approaches to scrub and augment the data–adding any missing values in the dataset, helped in understanding the behaviour of the lost person and in determining what significant variables enhanced their survivability. Linear regression was utilized to acquire the correlation among the numeric values in the database. The analysis indicated that there was no significant correlation among the independent variables; however, the data indicated that the wanderer tended to be found closer to where they left or were last seen. Logistic regression was used to investigate the survivability using three classification models. Finally, a framework is presented considering all the factors form the field tests and data analysis. Title: How to build and deploy machine learning models in the scalable cloud  Abstract: Machine learning model development is a skill taught at schools and is a good skill to have but where most of the student’s lake is how to serve these models to the clients. How to scale. Make sure that the server does not die if it gets a million hits in a second. How to build security around it. Agenda: Interested students who want to build along with me, can bring their laptop with MobaXterm installed and we can do the following together. login to a cloud environment (I will provide the cloud login credentials during the presentation) create a virtual environment for development build a semantic search engineby pulling libraries from the net pick a visualization and presentation method from D3JS develop an application using MVC pattern like the flask wrap the application in a docker container install scalable web engine like NGINX host it to the cloud (azure) provide secure access with a username and password to anyone on the internet This presentation will expose the tools required to build scalable machine learning applications in the cloud. Registration: Please visit https://forms.gle/7ZoimYgVjjpC9mag8 to register. Biographies: Dalia Hanna Topic: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Dalia Hanna is a PhD Candidate in the Department of Computer Science, Ryerson University. She is a member of Ryerson’s Network-Centric Applied Research Lab, a multidisciplinary Computational Public Safety-focused research lab. She has a B.Sc. in Electronics and Communication Engineering and M.Sc. in Instructional Design and Technology with a specialization in Online Learning. Dalia is also a certified project management professional (PMP ® ) and a certified facilitator. Her research interest in utilizing technology tools for public safety, search and rescue, and emergency management operations. . Dalia authored several research papers and presented in national and international conferences. Mujahid Sultan Topic: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Mujahid Sultan is a senior computer scientist and enterprise architect with vast experience in machine learning, pattern recognition, deep learning, NLP, text synthesis, transcription, time-series forecasting and cloud-native developments (Python, microservices, APIs, Docker, Kubernetes). His current research focus: a) working to develop a robust clustering method with mathematical proofs b) improving learning from imbalanced data on graph-based deep learning backends (TensorFlow, Torch and CNTK), and c) building Machine Learning based dynamic SDN controllers. He has authored in high impact journals in fields of Machine Learning, Artificial Intelligence, Data Visualization, Genetics and Drug Discovery for Cancer, Requirements Engineering and Enterprise Architecture. His publications can be found at https://orcid.org/0000-0001-6721-4044 Areas of Expertise include: Regression, Clustering, Classification, Deep Learning, Convolutional and Recurrent Neural Networks (LSTMs), Natural Language Processing (NLP), Self-Organizing Maps (SOM), Topic Modeling and Parallel Processing. Expert in info visualization using matlab, matplotlib, D3js and plotly. Skills: Full-stack development: (Angular+Flask+Docker); Python: (Scikit-Learn, Keras, TensorFlow, NLTK, Spacy, NumPy, Matplotlib, SpaCy to name a few); MATLAB: (toolboxes: statistics, microeconomics, parallel processing, bioinformatics to name a few). Platform experience: Docker Containers and Kubernetes on AWS, Azure/Azure Stack and Google Cloud Platform. PaaS/IaaS: (AWS: (Elastic Beanstalk, Lambda, Poly, Sage-Maker), Azure ML, and Heroku).

  • 2D Game Development in Unity with C# – Session 1

    Online via Zoom

    On Monday, July 27, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 1”. Day & Time: Monday, July 27, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development. This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more! All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. In our first session, we will review basic programming concepts, object-oriented programming, and introduce best practices working with C# in the Unity environment. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • Introduction to NLP for Classification Task – Session 4

    Online via Zoom Toronto, Ontario Canada

    On Wednesday, July 29, 2020 at 6:00 p.m., IEEE Toronto WIE, Computational Intelligence Society, and IM/RA will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 4”. Day & Time: Wednesday, July 29, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society, IM/RA Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In this session, we will be focusing on RNN and LSTM. Register: Please visit https://events.vtools.ieee.org/m/236479 or https://events.vtools.ieee.org/m/236480 for more details and to register.

  • 2D Game Development in Unity with C# – Session 2

    Online via Zoom

    On Monday, August 3, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 2”. Day & Time: Monday, August 3, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development.  This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more!  All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. Session 2 of the 2D Game Development workshop series explores interfaces and interactability. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • 2D Game Development in Unity with C# – Session 3

    Online via Zoom

    On Monday, August 10, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 3”. Day & Time: Monday, August 10, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development.  This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more!  All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. Session 3 teaches the concept of game loops and scenes. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • 2D Game Development in Unity with C# – Session 4

    Online via Zoom

    On Monday, August 17, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 4”. Day & Time: Monday, August 17, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development.  This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more!  All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. Session 4 explores animations and the associated features in animating your player/enemies. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • 2D Game Development in Unity with C# – Session 5

    Online via Zoom

    On Monday, August 24, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 5”. Day & Time: Monday, August 24, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development.  This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more!  All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. Session 5 focuses on polishing your 2D game. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • MAC Protocol Design for IoT Applications

    Virtual – Zoom

    On Tuesday, August 25, 2020 at 7:00 p.m., IEEE Toronto Computational Intelligence Society will be hosting “MAC Protocol Design for IoT Applications”. Day & Time: Tuesday, August 25, 2020 7:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto Computational Intelligence Society Location: Virtual – Zoom Contact: Lian Zhao Abstract: In this presentation, we introduce media access control (MAC) protocol design for two IoT applications, i.e., vehicle-to-vehicle (V2V) safety message broadcast in connected vehicles and smart factory in industry IoT. For each considered application, we investigate its unique communication characteristics, design our MAC protocol accordingly, and model and analyze the performance of the proposed design. For the V2V safety message broadcast, we develop a fully distributed MAC that achieves substantially lower delay and collision probability compared to existing distributed MAC designs. For the smart factory application, we develop a centralized MAC that can support a large number of devices with a single communication channel while satisfying stringent delay and collision requirements. Through the two examples, we demonstrate the potential of MAC design innovations in supporting emerging IoT applications. Register: Please visit https://events.vtools.ieee.org/m/237813 for more details and to register.

  • Introduction to Python Programming

    Virtual

    This is an introduction to Python programming for students without any prior programming knowledge or experience. The proposed 5-day course covers the fundamental aspects of programming, which include data types, various operators, input/output, conditions, control flow, functions, and algorithms. The learning experience is enhanced by a number of examples and problem sets (data, strings, file processing and simple graphics) that will be solved interactively during the lecture with the participation of the students. The course format includes 3 hours of daily lectures. Course Objective: Attendees will gain a solid understanding of principles of programing using Python; they can progress to more advanced programming topics and explores algorithms that are integral parts of more sophisticated methodologies, e.g., Artificial Intelligence. Attendees will have the knowledge to write various Python programs, and to design algorithms manipulating files and different types of data including numbers, and text. Note: This course is designed to be offered online, and it requires the attendees to use their personal computers/laptops. Details to Join in will be forwarded to Registered Attendees Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields. What will you receive after completion: A certificate of completion will be given to the students who successfully complete the course and pass a short exam. Electronic copies of the course materials. Attendees will also be provided with career, and skills development advice. Speaker Dr. Alireza Sadeghian Dr. Alireza Sadeghian has been with the Department of Computer Science at Ryerson University since 1999, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, and serves as the AI research Theme Lead in Healthcare and Analytics at the Institute for Biomedical Engineering, Science, and Technology. Dr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory and has extensive expertise in the areas of AI, machine learning, and Deep Learning particularly related to industrial and medical applications. He has supervised 9 postdoctoral fellows, 8 PhD, and 24 Master’s students, as well as 60 research assistants. He has published over 150 journal manuscripts, refereed conference papers, and book chapters, as well as two edited books. He has 2 invention disclosures and 2 patents. Dr. Sadeghian has been actively involved with a number of international professional and academic boards including IEEE Education Activity Board. Presently, he is the Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. Email: dr.alireza.sadeghian@ieee.org Agenda Day 1 – June 7, 2021, 6:00-9:00 pm: Introduction to computer systems, hardware architecture, CPU, memory, compilation, high level vs. low-level programming language, data representation, Python and PyCharm interactive IDE installation, writing/editing/saving/retrieving and running a simple program, basic data types, variables, assignments, comments, and expressions. The material learned will be reinforced through examples provided during the lecture. Day 2 – June 8, 2021, 6:00-9:00 pm: The following topics will be discussed: conditions, operators (arithmetic, logic, and comparison), control statements (if and if-else), and loops (for and while). The material learned will be reinforced through examples provided during the lecture. Day 3 – June 9, 2021, 6:00-9:00 pm: Students will be introduced to Strings and text files in Python. They will learn how to work with files, reading/writing text and numbers from/to a file, string manipulation, indexing, and string slicing. The material learned will be reinforced through examples provided during the lecture. Day 4 – June 10, 2021, 6:00-9:00 pm: Functions, arguments, and return values will be discussed. The material learned will be reinforced through examples provided during the lecture. Day 5 – June 11, 2021, 6:00-9:00 pm: The topics of lists and dictionaries will be discussed. Students will learn about the basic operators, creating, accessing, slicing, adding, removing, replacing, and iteration methods for lists and dictionaries. The material learned will be reinforced through examples provided during the lecture.

  • Introduction to Python programming – Registration

    Virtual

    This is an introduction to Python programming for students without any prior programming knowledge or experience. The proposed 5-day course covers the fundamental aspects of programming, which include data types, various operators, input/output, conditions, control flow, functions, and algorithms. The learning experience is enhanced by a number of examples and problem sets (data, strings, file processing and simple graphics) that will be solved interactively during the lecture with the participation of the students. The course format includes 3 hours of daily lectures (2 hours of lecture and 1 hour of lab). A certificate of completions will be given to the student who successfully complete the course and pass a short exam at the end of the course to evaluate their knowledge. Electronic copies of the course materials will be provided to the students. The students will also be provided with career advice, and skills development. The course is delivered online and limited space (25 spots) is available. Please register by July 11. After the registration, applicants will be contacted with the virtual meeting information and course material prior to the start of the course. Fees: - $250 CAD (IEEE or OSPE Members) - $350 CAD (Non-members) Please follow IEEE on Social Media: https://twitter.com/ieeetoronto https://www.ieeetoronto.ca/ Course Objective: Attendees will gain a solid understanding of principles of programing using Python; they can progress to more advanced programming topics and explores algorithms that are integral parts of more sophisticated methodologies, e.g., Artificial Intelligence. Attendees will have the knowledge to write various Python programs, and to design algorithms manipulating files and different types of data including numbers, and text. Note: This course is designed to be offered online, and it requires the attendees to use their personal computers/laptops. Details to Join in will be forwarded to Registered Attendees Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields. What will you receive after completion: A certificate of completion will be given to the students who successfully complete the course and pass a short exam. Electronic copies of the course materials. Attendees will also be provided with career, and skills development advice. Speaker Dr. Alireza Sadeghian Dr. Alireza Sadeghian has been with the Department of Computer Science at Ryerson University since 1999, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, and serves as the AI research Theme Lead in Healthcare and Analytics at the Institute for Biomedical Engineering, Science, and Technology. Dr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory and has extensive expertise in the areas of AI, machine learning, and Deep Learning particularly related to industrial and medical applications. He has supervised 9 postdoctoral fellows, 8 PhD, and 24 Master’s students, as well as 60 research assistants. He has published over 150 journal manuscripts, refereed conference papers, and book chapters, as well as two edited books. He has 2 invention disclosures and 2 patents. Dr. Sadeghian has been actively involved with a number of international professional and academic boards including IEEE Education Activity Board. Presently, he is the Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. Email: dr.alireza.sadeghian@ieee.org Agenda Day 1 – June 7, 2021, 6:00-9:00 pm: Introduction to computer systems, hardware architecture, CPU, memory, compilation, high level vs. low-level programming language, data representation, Python and PyCharm interactive IDE installation, writing/editing/saving/retrieving and running a simple program, basic data types, variables, assignments, comments, and expressions. The material learned will be reinforced through examples provided during the lecture. Day 2 – June 8, 2021, 6:00-9:00 pm: The following topics will be discussed: conditions, operators (arithmetic, logic, and comparison), control statements (if and if-else), and loops (for and while). The material learned will be reinforced through examples provided during the lecture. Day 3 – June 9, 2021, 6:00-9:00 pm: Students will be introduced to Strings and text files in Python. They will learn how to work with files, reading/writing text and numbers from/to a file, string manipulation, indexing, and string slicing. The material learned will be reinforced through examples provided during the lecture. Day 4 – June 10, 2021, 6:00-9:00 pm: Functions, arguments, and return values will be discussed. The material learned will be reinforced through examples provided during the lecture. Day 5 – June 11, 2021, 6:00-9:00 pm: The topics of lists and dictionaries will be discussed. Students will learn about the basic operators, creating, accessing, slicing, adding, removing, replacing, and iteration methods for lists and dictionaries. The material learned will be reinforced through examples provided during the lecture.

  • Digital Health and Health Technology Assessment

    Virtual: https://events.vtools.ieee.org/m/353132

    Digital Health and HTA (Health Technology Assessment) - Organized by the IEEE Computational Intelligence Digital Health provides unique opportunities to strengthen health systems and includes a range of technologies and services. These services and technologies have increasingly been used in the health sector because of their impact on patient-centered outcomes and value in healthcare decision-making. Digital health technologies depending on the application, target groups, and outcomes, can be comparators of traditional health technologies or used as an add-on to increase the effectiveness of those health interventions. Such technologies need to be reimbursed by public and private payers sooner or later. This talk is about digital health reimbursement of health and digital health technologies, the barriers to using digital health, and some potential solutions in the health systems. Keywords: Digital health, health technology assessment Speaker(s): Dr. Pooyeh Graili, Virtual: https://events.vtools.ieee.org/m/353132